Search: “tls-1.3”

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Cisco Secure Firewall Threat Defense Software TLS 1.3 Denial of Service Vulnerability

A TLS 1.3 buffer management flaw in Cisco Secure Firewall Threat Defense lets remote attackers crash the LINA process and reload devices.

A vulnerability in the TLS 1.3 implementation of Cisco Secure Firewall Threat Defense (FTD) software allows an unauthenticated remote attacker to cause a denial of service via crafted TLS 1.3 packets sent to a TLS 1.3-enabled listening socket. Improper buffer management causes the LINA process to crash, forcing a device reload that can occur before or after connection authentication. Cisco has released software updates to address the flaw.

Cisco Security Advisories·Sep 16, 16:00 UTC · 12h agoAdvisory 9 sources

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OpenSSL 4.1.0 Alpha1 Released With DTLS 1.3 and Faster Post-Quantum Cryptography

OpenSSL 4.1.0 Alpha1 adds DTLS 1.3 support, ML-DSA and ML-KEM post-quantum optimizations, and GREASE TLS compatibility, intended for testing only.

The alpha preview of OpenSSL 4.1.0 implements RFC 9147 DTLS 1.3 for UDP-based applications and integrates DTLS into the SSL listener API. It accelerates ML-DSA signatures and ML-KEM encapsulation with AVX-512 and VAES optimizations on x86_64, and adds GREASE (RFC 8701), IKEv2 KDF support, and Elbrus2000 (e2k) targets. The release is intended for testing and development, not production, and removes Windows-on-Itanium and Windows CE build targets.

Cyber Security News·Sep 10, 11:22 UTC · 6d agoTools

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OpenSSL’s new alpha build speeds up post-quantum crypto

OpenSSL 4.1.0 alpha1 adds DTLS 1.3 support and speeds up ML-DSA and ML-KEM post-quantum operations across several architectures.

The OpenSSL project released the first alpha of OpenSSL 4.1.0, months before general availability. The build adds DTLS 1.3 (RFC 9147) to secure UDP-based traffic such as VPNs, video calls and IoT, and includes optimized ML-DSA and ML-KEM operations for ppc64le, s390x and x86_64 plus AVX-512 acceleration for SHAKE hashing and AES-CBC decryption. Breaking changes include a new Net::Curl::Easy dependency for tsget, dropped Windows-on-Itanium and Windows CE support, and replacement of the no-ecdsa/no-ecdh Configure options with no-ec. It also adds GREASE support (RFC 8701), a DTLS mode for the SSL listener API, IKEv2 KDF support, and initial Elbrus2000 processor architecture support.

Help Net Security·Sep 9, 22:15 UTC · 7d agoTools

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Signing TLS handshakes inside a TPM

Blog post demonstrates signing TLS handshakes in Go with a TPM-held private key; full text was unavailable behind an Anubis challenge.

The title indicates a technique write-up on using a TPM-protected private key to sign TLS handshakes from Go. The full article text was not retrievable because the site serves an Anubis Hashcash-style proof-of-work challenge to automated fetchers, so no additional technical details (code, library, or threat model) could be extracted at collection time.

Lobsters · security·Sep 7, 14:54 UTC · 9d agoResearch

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Harnessing LLMs for Automating BOLA Detection

Unit 42's BOLABuster methodology uses LLMs to automate detection of broken object-level authorization vulnerabilities, uncovering flaws in Grafana, Harbor, and Easy!Appointments.

Palo Alto Unit 42 details BOLABuster, a methodology combining large language models with heuristics to automate detection of broken object-level authorization (BOLA) flaws, which traditional fuzzing and static analysis struggle to find. The approach uses LLM reasoning to understand application logic, map endpoint dependency relationships, and generate and interpret test cases. It found CVE-2024-1313 in Grafana, CVE-2024-22278 in Harbor, and 15 CVEs in Easy!Appointments. The team is continuing to hunt for BOLAs in open-source and internal projects.

Palo Alto Unit 42·Aug 17, 12:34 UTC · Aug 17, 2026ResearchCVE-2024-1313CVE-2024-22278CVE-2023-3285+14 CVEs

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TPMSpy: Validation of Measured Boot Systems by Low-Level Tracing of TPM Usage

Researchers present TPMSpy, a platform-agnostic method validating TPM Measured Boot via low-level tracing, finding inconsistent Linux systemd measurements that break remote attestation and LUKS decryption.

An arXiv paper (2609.05011) introduces TPMSpy, a method that analyzes virtualized system–TPM interactions to independently reconstruct and validate TPM Event Logs without relying on the quoting mechanism, applicable to open and closed systems and demonstrated on Linux and Windows. A longitudinal analysis of Linux systems running systemd versions 245–258 (2020–2025) found wide divergence in Measured Boot usage, undocumented behavioral changes, and no common usage pattern. The authors report inconsistent measurement of user-space systemd services, which prevents reliable remote attestation and LUKS disk decryption on affected systems.

arXiv cs.CR·Sep 4, 11:23 UTC · 12d agoResearch

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Session Attestation for Unmodified TLS Services in Confidential Virtual Machines

SessionLatch adds session attestation to unmodified TLS services in confidential VMs, cutting short-upload latency 63.1% versus TNG on Hygon CSV.

SessionLatch provides session attestation for confidential virtual machines without modifying applications, TLS implementations, or certificates. It relies on trusted observation of the server's locally generated ephemeral public key combined with standard TLS key confirmation, moving attestation integration to the operating system via a temporary latch that overlaps evidence exchange with the TLS handshake. Implemented with Linux and Windows integrations and evaluated on real Hygon CSV attestation, it reduces short-upload mean latency by 63.1%/23.0% relative to TNG in interleaved Linux/Windows experiments, while preserving enterprise service authentication and the native TLS data path, and supports mutual attestation.

arXiv cs.CR·Sep 9, 03:36 UTC · 8d agoResearch

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Redis security advisory (AV26-859)

Canada's Cyber Centre flagged a use-after-free in Redis 8.0's TLS handling, fixed in versions 8.2.9, 8.4.6, 8.6.6, 8.8.2, and 8.10.1.

Canada's Cyber Centre issued advisory AV26-859 for a use-after-free bug in Redis's tlsProcessPendingData() pending-list iteration, affecting the Redis 8.0 series. Fixed releases include 8.2.9, 8.4.6, 8.6.6, 8.8.2, and 8.10.1. Users and administrators are encouraged to review vendor guidance and update. No CVE identifier or exploitation details were provided in the advisory text.

Canadian Centre for Cyber Security·Aug 28, 14:34 UTC · 19d agoAdvisory

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VU#431093: TCG TPM 2.0 reference code found vulnerable to information leakage and timing side-channel attacks

CERT/CC discloses two TPM 2.0 reference code flaws allowing RSA key decryption and forged TPM attestations via crafted commands.

CERT/CC published VU#431093 covering two vulnerabilities in the TCG TPM 2.0 reference implementation: CVE-2026-6726 (information leakage via falsified TPM keys) and CVE-2026-6727 (timing side-channel in RSA OAEP decryption). An attacker with privileged access to a TPM command interface could send crafted TPM commands to decrypt ciphertexts for affected TPM-managed RSA keys, including the RSA Endorsement Key, or obtain credentials enabling forged TPM 2.0 attestations. Remediation is tracked in TCGVRT010 and TCGVRT0011.

CERT/CC Vulnerability Notes·Aug 11, 15:12 UTC · Aug 11, 2026VulnerabilityCVE-2026-6726CVE-2026-6727

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One Symptom, Three Levers: A Critical Review of On-Policy Self-Distillation

A review paper frames on-policy self-distillation collapse as governed by three levers: token weighting, privileged information, and guidance decay.

The paper critically reviews On-Policy Self-Distillation (OPSD), where a language model trains on its own generations scored token-by-token by a teacher conditioned on privileged information such as reference solutions or environment feedback. It identifies collapse, the progressive narrowing of producible reasoning paths, as the dominant failure mode and analyzes it through three levers: signal weighting, the nature of privileged information, and teacher dynamics. The review is restricted to mathematical reasoning, reports no new experiments, and offers a shared vocabulary separating settled findings from disputed ones.

Hugging Face daily papers·Aug 25, 20:00 UTC · 22d agoAI research

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MaxKernel: Agentic Kernel Generation for TPUs

Researchers open-source MaxKernel, a multi-agent LLM system that generates and optimizes TPU kernels matching expert hand-tuned baselines on JaxBench.

MaxKernel is a multi-agent system offering three paradigms for TPU kernel development: human-in-the-loop collaborative design, a fully autonomous metric/trace-driven optimization loop, and graph-based autonomous search for global exploration. All paradigms draw on a shared pool of specialized sub-agents for planning, implementation, self-debugging, testing, and hardware profiling. Evaluated on JaxBench's 50 diverse TPU kernel tasks and real-world workloads from open-source models, it consistently matches expert hand-tuned baselines. The system is open-sourced via the AI-Hypercomputer GitHub repository.

Hugging Face daily papers·Sep 2, 20:00 UTC · 14d agoAI tools & infra

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A Deep Dive Into Attempted Exploitation of CVE-2023

Mirai-like botnet scans exploit TP-Link EOL router flaw CVE-2023-33538 after CISA KEV addition, though observed exploit code is flawed.

Unit 42 observed large-scale automated scans attempting to exploit CVE-2023-33538 in end-of-life TP-Link TL-WR940N, TL-WR740N and TL-WR841N routers after CISA added the flaw to its KEV catalog in June 2025. HTTP GET requests inject commands via the ssid1 parameter at the /userRpm/WlanNetworkRpm endpoint to download and execute an arm7 ELF binary, a Mirai variant related to the Condi IoT botnet. Firmware emulation and reverse engineering showed the observed exploits are flawed and would fail, but the underlying vulnerability is real and successful exploitation requires authentication to the router's web interface. TP-Link confirmed the devices are end-of-life with no patches available and recommends replacing units and eliminating default credentials.

Palo Alto Unit 42·Aug 19, 12:03 UTC · 28d agoExploit / PoC in the wildCVE-2023-335381

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Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security Labs·Sep 11, 00:00 UTC · 6d agoResearch

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CVE-2026-86304: MojoX::Authentication versions before 0.006 for Perl allow SAML authentication bypass because parse_assertion builds Net::SAML2::Binding::POST without a trust anchor

MojoX::Authentication before 0.006 for Perl allows SAML authentication bypass because parse_assertion builds Net::SAML2::Binding::POST without a trust anchor (CVE-2026-86304).

CVE-2026-86304 affects MojoX::Authentication versions before 0.006 for Perl. The parse_assertion function builds Net::SAML2::Binding::POST without a trust anchor, so SAML assertions are not validated against a trusted signing key, enabling authentication bypass. The flaw is fixed in version 0.006 of the module.

oss-security·Sep 6, 23:14 UTC · 10d agoVulnerabilityCVE-2026-86304

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Version Control DFIR: a Cheatsheet to GitHub, GitLab, Bitbucket, and Azure DevOps

Wiz published a DFIR cheatsheet covering log visibility, incident readiness, and threat hunting across GitHub, GitLab, Bitbucket, and Azure DevOps.

Wiz researchers released a practitioner's guide to version control system forensics, incident response, and threat hunting. The cheatsheet maps log sources, audit capabilities, and hunting workflows across GitHub, GitLab, Bitbucket, and Azure DevOps. It aims to improve incident readiness for source code and CI/CD compromise scenarios.

Wiz Blog·Aug 27, 12:00 UTC · 20d agoResearch1

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Breaking the 1.58-bit Barrier for Ternary LLMs

An arXiv paper claims a method that breaks the 1.58-bit barrier for ternary large language models.

The arXiv preprint 2609.16338, titled 'Breaking the 1.58-bit Barrier for Ternary LLMs,' presents research on ternary-weight large language models, which use roughly 1.58 bits per weight. The source text contained only the title and Hacker News engagement data (56 points, no comments), so further technical details are not available.

Hacker News · AI·Sep 16, 20:59 UTC · 7h agoAI researchHN 56↑ · 0 comments

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The Illusion of Local Privacy: Confidentiality Boundary Failures in Consumer LLM Serving Systemsnew

Researchers show local LLM serving systems leak prompts via memory residue, plaintext persistence, a llama.cpp tenant-isolation flaw, and timing oracles.

A study of consumer local-LLM serving systems identifies four boundaries where prompt confidentiality fails: model loading, runtime memory, wrapper persistence, and the serving interface. Using the LLAnalyzer framework across four open-weight model families and two deployment platforms, the authors recover plaintext prompts from allocator-managed memory after inference and show wrappers extend prompt lifetime. They also uncover a previously undocumented llama.cpp authorization flaw letting one authenticated client restore another tenant's saved conversation state, succeeding in 200/200 trials, plus a remote timing oracle via shared prompt-prefix caching that works over WAN.

arXiv cs.CR·Sep 16, 11:53 UTC · 16h agoAI safety & security

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Hackers Exploit FortiGate SSL-VPN Flaw to Breach Thai ISP and Deploy MeshCentral Backdoor

Threat actors exploited FortiOS SSL-VPN flaw CVE-2024-21762 to breach Thai ISP Triple T Broadband, gaining root-level persistence via MeshCentral agents.

Attackers exploited CVE-2024-21762, an out-of-bounds write enabling unauthenticated RCE in FortiOS SSL-VPN, against Triple T Broadband's FortiGate 60F at mail.3bb.co.th, launching a Node.js reverse shell via a ROP payload. Hunt.io uncovered the operation through an exposed staging directory at 92.63.180[.]133:8888 containing 298 files of exploits, credential-harvesting scripts, session cookies, and a device inventory. Post-compromise, the actors deployed MeshCentral agents (device group TH-3BB, C2 www.ayuthayatech.com) running as root, plus a hidden SUID backdoor at /usr/local/bin/.rc, and also targeted an internal Pentaho/Tomcat server with Ghostcat (CVE-2020-1938). A cleanup script removed logs, shell histories, and web shells while deliberately preserving the MeshCentral agent and SUID backdoor.

GBHackers·Sep 15, 05:20 UTC · 1d agoExploit / PoC in the wild 3 sourcesCVE-2024-21762CVE-2020-1938

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Reference-Based Bias Detection in LLMs via Relative Representations of Hidden States

Researchers propose auditing LLM bias via relative hidden-state representations, detecting bias increases with 3-50x less compute than output-level benchmarks.

The paper introduces a reference-based bias auditing method that compares hidden-state representations across model variants, such as before and after fine-tuning, by encoding sentences relative to a fixed anchor set. The resulting Representational Bias Shift (Delta-B) correlates with output-level bias change in 15 of 18 tested settings, reaching |r| = 0.84 under full fine-tuning across WildGuardMix, DecodingTrust, and ToxiGen benchmarks. Thresholding Delta-B detects checkpoints whose bias increased with ROC AUC between 0.65 and 0.99 and beats a SEAT-based baseline, while auditing a model in about three minutes with 3-50x less compute.

Hugging Face daily papers·Sep 8, 20:00 UTC · 8d agoAI research1

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Detecting cloud ransomware in Azure with Tenable One’s cloud detection and response capabilities

Tenable details ransomware group Storm-0501's Azure tenant-hijacking tactics and how its cloud detection and response identifies them.

Tenable's blog describes how cybercrime group Storm-0501 conducts cloud-first ransomware campaigns against Azure environments. The group has shifted from endpoint encryption to total hijacking of cloud tenants and systematically neutralizes resource locks, immutability policies, and backups. Tenable outlines its One Cloud Exposure detections, using AI-powered threat stories and precision alerts, to expose these TTPs early.

Tenable Blog·Aug 17, 15:15 UTC · Aug 17, 2026Threat actor in the wild

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Notes on gotchas while migrating 35kb preprompts from Opus to self-hosted Ollama

Opinion piece urges migrating 35KB preprompts from Anthropic/OpenAI to self-hosted Ollama, citing session privacy risks and safety filters blocking security research.

The author documents gotchas migrating 35KB preprompts from Claude Opus to self-hosted Ollama, motivated by fears that frontier providers train on user sessions, citing the OpenAI Navier-Stokes controversy. The piece argues inference providers cannot audit their own retention or training pipelines and that only self-hosted hardware offers verifiable privacy. It also criticizes frontier safety filters for refusing vulnerability research tasks and calls for models that support exploitability testing in CI/CD pipelines.

Hacker News · AI·Sep 14, 13:59 UTC · 2d agoAI industryHN 41↑ · 13 comments1

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Safety for Whom? Boundary-Aware Self-Distillation for Controlled LLM Safety Refusal

A self-distillation safety framework tunes narrow-boundary refusals in Qwen3-8B, raising target-domain refusal to 84.75% while cutting over-refusal from 15.20% to 5.20%.

The paper formulates narrow-boundary safety, where deployments need refusals within specific topics rather than whole subjects, and proposes an offline self-generated framework with controlled topic generation, escalating retries, and harmful-benign boundary pairs. On political persuasion with Qwen3-8B, the method raised target-domain refusal from 9.47% to 84.75% and cut the mean unsafe-response rate across three broader benchmarks from 26.26% to 0.14%. Verified target-model responses reduced over-refusal from 15.20% to 5.20%, and boundary-pair data cut comply-side over-refusal on held-out pairs from 32.94% to 4.16%. Results show data composition controls the safety-usability trade-off and alignment should be evaluated on both sides of the refusal boundary.

Hugging Face daily papers·Sep 2, 20:00 UTC · 14d agoAI safety & security1

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Fluid Notarization: Verifiable Evolution of Concurrently Edited Structured Documentsnew

Fluid Notarization anchors delta-CRDT change graphs on blockchain, providing verifiable provenance for concurrently edited documents, demonstrated on collaborative electronic health records.

The paper introduces Fluid Notarization, a paradigm that notarizes the evolution of collaboratively edited structured documents rather than isolated snapshots. It builds on Melda, a JSON-native delta-CRDT representing changes as compact content-addressed deltas linked by causal dependencies, with blockchain notarization reduced to recording identifiers of evolution artifacts while synchronization, reconstruction, and conflict resolution remain off-chain. The architecture combines deterministic CRDT convergence with independently auditable proof-of-existence, provenance, and publication evidence, validated through a prototype based on collaboratively edited electronic health records.

arXiv cs.CR·Sep 16, 16:20 UTC · 12h agoResearch

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CVE-2026-86219: Authen::SASL::Perl::DIGEST_MD5 versions before 2.2100 for Perl accept replayed authentication responses via unverified nonce in server_step

Authen::SASL::Perl::DIGEST_MD5 before 2.2100 for Perl accepts replayed DIGEST-MD5 authentication responses via unverified nonce handling (CVE-2026-86219).

CVE-2026-86219 affects Authen::SASL::Perl::DIGEST_MD5 versions before 2.2100 for Perl. The server_step function does not verify the nonce, allowing replayed authentication responses to be accepted in DIGEST-MD5 SASL exchanges. The fix is available in version 2.2100 of the perl-authen-sasl distribution.

oss-security·Sep 6, 18:55 UTC · 10d agoVulnerabilityCVE-2026-862191

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Towards Scalable and Cost-Efficient Vulnerability Detection: A Study on Automatic Query Generation

A study finds LLM-synthesized CodeQL queries improve average F1-score by 82% over baseline queries, offering scalable vulnerability detection versus direct LLM scanning.

Researchers conducted an empirical study evaluating whether LLMs can synthesize executable CodeQL queries from National Vulnerability Database vulnerability data. LLM-generated queries significantly enhanced baseline CodeQL suites, yielding an 82% improvement in average F1-score across a diverse set of real-world vulnerabilities. A cost-benefit analysis shows direct LLM-based scanning of entire repositories is often computationally and financially prohibitive, while LLM query synthesis offers a scalable and cost-effective alternative for large-scale vulnerability detection.

arXiv cs.CR·Sep 9, 16:31 UTC · 7d agoResearch1

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PrivEscalate: Measuring and Augmenting the Threat of LLM-Automated Linux Privilege Escalation

Researchers release PrivEscalate, a 531-scenario benchmark showing LLM agents' Linux privilege-escalation success varies by vulnerability class, plus PrivEscAgent, a domain-specialized agent that boosts success.

The paper introduces PrivEscalate, an open-source benchmark of 531 Dockerized Linux privilege-escalation scenarios spanning 14 sub-categories, plus 329 parameterized variants measuring sensitivity to environmental distractors. Evaluating six LLMs across three agent architectures shows capability is heterogeneous across vulnerability classes, sensitive to perturbation, and architecture-dependent. The authors also present PrivEscAgent, a wrapper adding deterministic enumeration, category matching, and step planning that outperforms prior privesc-agent baselines without modifying the underlying LLM. The benchmark is released to support LLM agent evaluation, defensive tool validation, and red-team training.

arXiv cs.CR·Sep 8, 17:34 UTC · 8d agoResearch

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AutoTrans: AI-Assisted Automatic Translation of Security Assertions for RISC-V Processors

AutoTrans uses LLMs with regex extraction and formal verification to automatically translate security assertions across RISC-V processors, achieving 78% unattended acceptance.

AutoTrans is an automated framework for translating verified security assertions between RISC-V processor targets, where manual translation takes hours per assertion. It combines a regex-based SystemVerilog signal extractor to prevent LLM signal hallucination, a pinned prompt template yielding byte-identical prompts resilient to model updates, and JasperGold FPV formal verification of generated assertions. Applied with DeepSeek V4 to translate assertions between RISC-V targets such as IBEX and NS31A, it achieves a 78% automatic translation acceptance rate without human intervention and 100% after human refinement.

arXiv cs.CR·Sep 9, 11:31 UTC · 7d agoResearch

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Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation

TGOPD verifies teacher reliability per prompt before on-policy distillation, outperforming vanilla OPD across math, code, and instruction benchmarks.

Teacher-Gated On-Policy Distillation (TGOPD) estimates teacher reliability from verifier-scored teacher probes and routes each prompt either to dense on-policy distillation or to verifier-grounded GRPO, avoiding misleading updates from confidently wrong teachers under mode-seeking reverse KL. Across 4B and 35B students in mathematics, code, and instruction following, TGOPD outperforms vanilla OPD in all six single-domain settings and achieves higher seven-benchmark averages under multi-domain training. It also raises teacher-node GPU utilization from 9.8% to 78.9% in the measured 4B single-domain run by reusing idle teacher capacity.

Hugging Face daily papers·Sep 1, 20:00 UTC · 15d agoAI research

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T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks

T1, a 122B MoE terminal agent trained with reinforcement learning, reaches 64.0% on Terminal-Bench 2.1, surpassing GPT-5.4 and GLM-5.1 on long-horizon tasks.

T1 is a 122B mixture-of-experts model trained with reinforcement learning to operate a real shell in a cloud sandbox for up to 300+ tool-call turns per task, rewarded by executing each task's own verifier. The recipe combines aggressive warm starts, dense process rewards, TITO construction, and rollout routing replay, cutting the training-to-inference log-probability difference from 0.021 to 0.013 with zero token drift. Training used an out-of-distribution corpus disjoint from Terminal-Bench 2.1. Post-training raised the base model from 43.8% to 64.0% resolved on Terminal-Bench 2.1 and 27.9% on Long-Horizon Terminal Bench.

Hugging Face daily papers·Sep 9, 20:00 UTC · 7d agoAI research1

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